Critical Multipliers in Variational Systems via Second-order Generalized Differentiation
Boris S. Mordukhovich, M. Ebrahim Sarabi

TL;DR
This paper introduces the concepts of critical and noncritical multipliers in variational systems, providing characterizations and conditions for stability and convergence in optimization algorithms using second-order generalized differentiation.
Contribution
It extends the notions of critical multipliers to a broad variational framework and offers complete characterizations using second-order subdifferential theory.
Findings
Noncritical multipliers are equivalent to error bounds in perturbed systems.
Critical multipliers can be eliminated through full stability conditions.
Lipschitz-like properties imply robust isolated calmness of solution maps.
Abstract
In this paper we introduce the notions of critical and noncritical multipliers for subdifferential variational systems extending to a general framework the corresponding notions by Izmailov and Solodov developed for classical Karush-Kuhn-Tucker (KKT) systems. It has been well recognized that critical multipliers are largely responsible for slow convergence of major primal-dual algorithms of optimization. The approach of this paper allows us to cover KKT systems arising in various classes of smooth and nonsmooth problems of constrained optimization including composite optimization, minimax problems, etc. Concentrating on a polyhedral subdifferential case and employing recent results of second-order subdifferential theory, we obtain complete characterizations of critical and noncritical multipliers via the problem data. It is shown that noncriticality is equivalent to a certain error…
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Taxonomy
TopicsOptimization and Variational Analysis · Advanced Optimization Algorithms Research · Topology Optimization in Engineering
